Triple
T3974935
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Wendell Phillips Garrison |
E85616
|
entity |
| Predicate | givenName |
P17
|
FINISHED |
| Object | Wendell |
E148262
|
NE FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Wendell | Statement: [Wendell Phillips Garrison, givenName, Wendell]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Wendell Context triple: [Wendell Phillips Garrison, givenName, Wendell]
-
A.
Wendell
chosen
Wendell is a masculine given name of English origin that gained prominence in the United States, notably borne by figures such as abolitionist orator Wendell Phillips.
-
B.
Weldon
Weldon is the middle name of James Weldon Johnson, the influential African American writer, civil rights activist, and leader of the NAACP.
-
C.
Ebersole
Ebersole is a surname most notably associated with American actress and singer Christine Ebersole.
-
D.
Leland
Leland is a masculine given name of English origin, historically associated with figures such as American industrialist and Stanford University founder Leland Stanford.
-
E.
Rilland
Rilland is a village in the Dutch province of Zeeland, located on the island of Zuid-Beveland.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69aed93908348190a26c8aaf4fab3e86 |
completed | March 9, 2026, 2:29 p.m. |
| NER | Named-entity recognition | batch_69aef9b511f88190afca12c77481b344 |
completed | March 9, 2026, 4:47 p.m. |
| NED1 | Entity disambiguation (via context triple) | batch_69b5401712188190aa6144dc1d5dcab6 |
completed | March 14, 2026, 11:01 a.m. |
Created at: March 9, 2026, 3:33 p.m.